Refining data into value

Refining data into value

The famous phrase “Data is the new Oil” turned 10 last year, and it endures as one of our favourites.

Data is oily in that it’s often idle and difficult to access. It sits just under the surface of company priorities, bubbling away in a murky unsexy form as it lies in wait for a recognition of its true potential. Upon its discovery, ecstatic shouts of excitement are not uncommon, as a whole new world of ROI rains down on the data-savvy few to appreciate it.

But, like Oil, Data must also be tapped to have true value.

In this post, Simon Small, our Director of Solutions, Support and Marketing, takes you through the three key challenges that are stopping companies from putting data to work.

1. CHOICE

The overwhelming potential of Big Data makes it extremely difficult to plan which activity is best to execute and how. This can paralyse teams and organisations who’re already extremely busy running, optimising and transforming with less. It takes time to wade through the opportunity, trial things, learn and move forward. Prediction, targeting, product strategy, testing, multi-channel optimisation, triggered comms, customer service, sales, brand building…. how do you mash all that together?

2. SYSTEMS

The second challenge is how to plug it together in a way that is usable by the people in the organisation, can be automated, is scalable and actually works. While most platforms will persuasively convince you they can plug in, turn on and start making you a disruptive organisation as easy as 1, 2, 3… they can’t. Well, they could in an ideal world, but we don’t live in an ideal world. Any platform is highly dependent on other platforms, quality data, seamless integration and a plan to utilise it all (see challenge 1) in a meaningful way. I’ve seen hundreds of product demos that fall flat as soon as you try to do something off sales script, or integrate in a slightly different way, or even do the thing they did in the seamless demo after they’ve gone. 😐

3. CAPABILITY

Finally, it all relies on people who can efficiently access, translate, apply and action data in meaningful ways. Yes, data scientists but also designers, developers, content creators, platform managers, leaders all in cross-functional ways. Argh. The myth of completely automated and intelligent marketing platforms is mostly forgotten but many still underestimate the human effort required to turn the cogs and convert potential into value.

Lexer makes data more human.

There is so much to Lexer (obvs) but the standout bits for me are how easy it is for humans to use the platform (this is a big deal) to help them understand the humans that they need to service.

They bring together disparate data sources into a single location and then make the customer/user records more detailed, nuanced and human through a unique process they call enrichment. Then an organisation can create groups of people based on these much more interesting data points and either understand them better or target them in much better ways.

Get in touch

Passionate about data or want to put it to work? I like coffee, let’s catch up.

Read a full version of this story, including Simon’s journey to Lexer over here.